Motion Planning Testing Environment for Robotic Skid-Steered Vehicles

One of the main goals of robotics research is to give physical platforms intelligence, allowing for the platforms to act autonomously with minimal direction from humans. Motion planning is the process by which a mobile robot plans a trajectory that moves the robot from one state to another. While th...

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Other Authors: Pace, James (authoraut)
Format: Others
Language:English
English
Published: Florida State University
Subjects:
Online Access:http://purl.flvc.org/fsu/fd/FSU_SUMMER2017_Pace_fsu_0071N_14099
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spelling ndltd-fsu.edu-oai-fsu.digital.flvc.org-fsu_5521112019-07-01T05:18:31Z Motion Planning Testing Environment for Robotic Skid-Steered Vehicles Pace, James (authoraut) Collins, Emmanuel G. (professor directing thesis) Clark, Jonathan E. (committee member) Ordonez, Camilo, 1979- (committee member) Shoele, Kourosh (committee member) Florida State University (degree granting institution) College of Engineering (degree granting college) Department of Mechanical Engineering (degree granting departmentdgg) Text text master thesis Florida State University English eng 1 online resource (66 pages) computer application/pdf One of the main goals of robotics research is to give physical platforms intelligence, allowing for the platforms to act autonomously with minimal direction from humans. Motion planning is the process by which a mobile robot plans a trajectory that moves the robot from one state to another. While there are many motion planning algorithms, this research focuses on Sampling Based Model Predictive Optimization (SBMPO), a motion planning algorithm that allows for the generation of trajectories that are not only dynamically feasible, but also efficient in terms of a user defined cost function (specifically in this research, distance traveled or energy consumed). To accomplish this, SBMPO uses the kinematic, dynamic, and power models of the robot. The kinematic, dynamic, and power models of a skid-steered robot are dependent on the type and inclination of the terrain over which the robot is traversing. Previous research has successfully used SBMPO to plan trajectories on different inclinations and terrain types, but with the terrain type and inclination being held constant over the trajectory. This research extends the prior work to plan trajectories where the terrain type changes over the trajectory and where the robot has the option to go over or around hills, situations extremely common in real world environments encountered in military and search and rescue operations. Furthermore, this research documents the design and implementation of a 3D visualization environment which allows for the visualization of the trajectory generated by the planner without having a robot follow the trajectory in a physical environment. A Thesis submitted to the Department of Mechanical Engineering in partial fulfillment of the requirements for the degree of Master of Science. Summer Semester 2017. July 7, 2017. Motion Planning, Robots, Simulation, Skid-steered Includes bibliographical references. Emmanuel G. Collins, Jr., Professor Directing Thesis; Jonathan Clark, Committee Member; Camilo Ordonez, Committee Member; Kourosh Shoele, Committee Member. Robotics Mechanical engineering Computer science FSU_SUMMER2017_Pace_fsu_0071N_14099 http://purl.flvc.org/fsu/fd/FSU_SUMMER2017_Pace_fsu_0071N_14099 http://diginole.lib.fsu.edu/islandora/object/fsu%3A552111/datastream/TN/view/Motion%20Planning%20Testing%20Environment%20for%20Robotic%20Skid-Steered%20Vehicles.jpg
collection NDLTD
language English
English
format Others
sources NDLTD
topic Robotics
Mechanical engineering
Computer science
spellingShingle Robotics
Mechanical engineering
Computer science
Motion Planning Testing Environment for Robotic Skid-Steered Vehicles
description One of the main goals of robotics research is to give physical platforms intelligence, allowing for the platforms to act autonomously with minimal direction from humans. Motion planning is the process by which a mobile robot plans a trajectory that moves the robot from one state to another. While there are many motion planning algorithms, this research focuses on Sampling Based Model Predictive Optimization (SBMPO), a motion planning algorithm that allows for the generation of trajectories that are not only dynamically feasible, but also efficient in terms of a user defined cost function (specifically in this research, distance traveled or energy consumed). To accomplish this, SBMPO uses the kinematic, dynamic, and power models of the robot. The kinematic, dynamic, and power models of a skid-steered robot are dependent on the type and inclination of the terrain over which the robot is traversing. Previous research has successfully used SBMPO to plan trajectories on different inclinations and terrain types, but with the terrain type and inclination being held constant over the trajectory. This research extends the prior work to plan trajectories where the terrain type changes over the trajectory and where the robot has the option to go over or around hills, situations extremely common in real world environments encountered in military and search and rescue operations. Furthermore, this research documents the design and implementation of a 3D visualization environment which allows for the visualization of the trajectory generated by the planner without having a robot follow the trajectory in a physical environment. === A Thesis submitted to the Department of Mechanical Engineering in partial fulfillment of the requirements for the degree of Master of Science. === Summer Semester 2017. === July 7, 2017. === Motion Planning, Robots, Simulation, Skid-steered === Includes bibliographical references. === Emmanuel G. Collins, Jr., Professor Directing Thesis; Jonathan Clark, Committee Member; Camilo Ordonez, Committee Member; Kourosh Shoele, Committee Member.
author2 Pace, James (authoraut)
author_facet Pace, James (authoraut)
title Motion Planning Testing Environment for Robotic Skid-Steered Vehicles
title_short Motion Planning Testing Environment for Robotic Skid-Steered Vehicles
title_full Motion Planning Testing Environment for Robotic Skid-Steered Vehicles
title_fullStr Motion Planning Testing Environment for Robotic Skid-Steered Vehicles
title_full_unstemmed Motion Planning Testing Environment for Robotic Skid-Steered Vehicles
title_sort motion planning testing environment for robotic skid-steered vehicles
publisher Florida State University
url http://purl.flvc.org/fsu/fd/FSU_SUMMER2017_Pace_fsu_0071N_14099
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